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Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, <https://doi.org/10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

copied from cf-staging / r-mcmc
Type Size Name Uploaded Downloads Labels
conda 1.4 MB | win-64/r-mcmc-0.9_6.1-r36h301d43c_0.tar.bz2  5 years and 2 months ago 1098 main cf202003
conda 1.4 MB | win-64/r-mcmc-0.9_6.1-r35h301d43c_0.tar.bz2  5 years and 2 months ago 1056 main cf202003
conda 1.4 MB | osx-64/r-mcmc-0.9_6.1-r35h0b31af3_0.tar.bz2  5 years and 2 months ago 333 main cf202003
conda 1.4 MB | osx-64/r-mcmc-0.9_6.1-r36h0b31af3_0.tar.bz2  5 years and 2 months ago 342 main cf202003
conda 1.4 MB | linux-64/r-mcmc-0.9_6.1-r36h516909a_0.tar.bz2  5 years and 2 months ago 3456 main cf202003
conda 1.4 MB | linux-64/r-mcmc-0.9_6.1-r35h516909a_0.tar.bz2  5 years and 2 months ago 3302 main cf202003

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